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2 INTRODUCTION Are you getting personal with your customers? If not, it s time to start. Online retailers see significantly greater results across a broad spectrum of metrics when they personalize the shopping experience to each customer. Consider one e-retailer, who boosted conversion rates by an astounding 340%: that kind of result personifies ecommerce success. Moreover, shoppers increasingly prefer a personalized experience 1 : 59% say that it is easier to find what they re looking for when retailers personalize. 40% indicate they buy more from retailers that personalize the shopping experience. 51% are willing to share data to receive a better shopping experience. Some experts even believe that retailers who fail to personalize will be unable to compete in the future marketplace. As more data becomes available and the cost of deriving insight from the data continues to drop, organizations that don t use it will simply not be able to compete, says Darren Vengroff, Chief Scientist at retail personalization specialist RichRelevance 2. But what is this concept called personalization? In this paper, we ll explore what personalization looks like and how it works. Then we ll lay out the action steps you can take immediately to start reaping the amazing rewards of selling with a personal touch in your own business. TABLE OF CONTENTS The Power of Personalization How to Personalize: Challenges, Considerations and Best Practices Action Steps: Actions You Can Take Through The Whole Buying Cycle Conclusion by OSF Global Services. All rights Reserved. Pg. 1

3 The Power of Personalization Personalization tailors the shopping experience to the customer Personalization improves a shopper's experience by offering relevant help in the form of better search results, specific product recommendations, or even product descriptions that help the buyer. This helps build long-term relationships. 3 Just imagine if you could predict what consumers wanted to buy before they even knew themselves, and then put it in front of them. The rewards for ecommerce retailers who cater to their customers preferences and personalities go beyond more conversions and larger orders: it s lifetime business. Over and over again, when retailers implement personalization strategies and techniques into their business practices, they see significant gains across a score of metrics. "The Holy Grail is having a customer for life, and having that customer buy from you repeatedly." Alex Zhardanovsky, Co-Founder, PetFlow Conversion Rate: Ace Tools increased conversion by 340% 4 Click-Through Rate: Laser Design, Inc. saw CTR jump threefold 5 Customer Lifetime Value: Personalization can boost CLV by 500%. 6 Order Amount: Wine.com saw the average order value rise by 15% 7 Total Sales: On average, total online sales increase 25%. 8 Purchase Frequency: Shoppers purchase 300% more often on average 9 All of these metrics generate accelerating revenue, that is, revenue that accumulates at multiple steps through the shopping process. The longer I can keep someone on my site, the more likely I can get them to buy something. And, if I can get them to buy something, I have a great shot at getting them to buy the accessories that go with it, says Maria Polidoro, owner of Ace Tools. Personalization makes online retailers more competitive Better yet, personalization better positions online retailers as a differentiating factor. It offers tangible value to customers an easier, less stressful, more successful shopping experience, and ecommerce sites that mold themselves around their customers experiences stand out. It certainly worked for Amazon: Amazon s former Manager of Consumer Behavior Research, David Selinger, notes, by OSF Global Services. All rights Reserved. Pg. 2

4 personalization was really important in enabling Amazon to differentiate itself and grow in the past ten years. 10 It is a lot easier for me to work with my existing customer and get extra value than to try and go after new customers. Maria Polidoro, Owner, Ace Tools Unfortunately, personalization is not simple. In fact, it s a highly technical process that must overcome several successive challenges before it can yield sales success: 1. Adequate, intelligent data collection 2. Effective data processing to extract usable information 3. Tactical use of that information throughout the shopping funnel The two grand-daddies of personalization are Amazon and Netflix, and they re great examples of the power of personalization. But they re also mega-corporations with access to extensive technological resources and prodigious amounts of raw data. What s a more modest ecommerce site to do? Luckily there s room for everyone to be competitive in this arena: since Amazon pioneered personalized recommendations a decade ago, there s been little innovation, but a lot of progress. Let s explore what that means for you. HOW: Personalization Best Practices Data Collection For most retailers, the first and toughest challenge to personalization is to procure enough data. In the absence of adequate data, customized recommendations and sales messaging are likely to perform no better than randomly selected offerings. Data that can be collected includes: Personal demographic data, such as age and location Purchase and wish list history Browsing history (on-site behavior) Personal preferences Product thumbs up or thumbs down Social data (such as Facebook likes ) Collecting this information is a careful balance of observation, direct questions and indirect prompts. According to DJ Patil of Greylock Partners, soliciting information through more of a conversation is a by OSF Global Services. All rights Reserved. Pg. 3

5 better approach than replicating the feel of a doctor s appointment where you are filling out your life history via forms. 11 For example, retailers can give shoppers the option to vote on the recommendations they see: do they get a thumbs up or thumbs down? That alone can yield tremendous usable data, both on individual shoppers and in aggregate. Better technology enables retailers to gain a better understanding of the individual. James Doman, marketing Manager, PredictiveIntent Data Collection Best Practices Treat info collection as a collaborative dialogue with your customer. Use data collected to generate business intelligence (see below). Play on human psychology: people love to correct things. 12 Use social graph data, especially as Facebook fine-tunes likes into more granular bought and want indicators Data Processing If getting the information is a challenge, wait until you have to start using it. Retailers face challenges on how to store and organize this data and then turn this into personal recommendations. The major problem with big data, especially in large quantities, is lack of structure. That means it s very difficult to track relationships between different data points. You can t do much without an infrastructure that collects, catalogs and organizes the data into targeting groups, writes online ad agency OwnerIQ CEO Jay Habegger 13 Retailers must take raw data points and translate them into actionable business intelligence. If a company can successfully extrapolate aggregate sales trends, executives can make more successful decisions in sales forecasting and merchandise planning. But aggregate data analysis is relatively simple compared to breaking it down for individual users. That requires segmenting the data, connecting the dots, drawing conclusions, and then serving up personalized recommendations and experiences and doing it all algorithmically and automagically. Let s illustrate. Collaborative filtering is an example of data processing where retailers make predictions (filtering) about user wants and needs by collecting data from many users (collaborating) and connecting the dots between all of the data points. In other words, if persons A and B share an opinion by OSF Global Services. All rights Reserved. Pg. 4

6 on a product, A is more likely to share B s opinion on a different product, than to share a randomly chosen person s opinion. As you can imagine, while the aim is straight-forward, the process is non-trivial. It requires significant amounts of data, plus the technical resources to process the information. It also requires people: specially trained engineers, data analysts, and/or third-party vendors with the appropriate skill sets and service offerings. Key Concepts Kind: Implicit data: gained from users actions on a website Explicit data: gained directly from user via surveys, etc. Structure: Organization; the ability to fit data into a relational database Insight: Raw data must be processed to derive actionable insight Intent: The real goal is to decode users purchasing intentions Indeed: it s all about intent. That s the concept at the heart of the data processing challenge. How do you extract intent to buy from a thumbs-up or thumbs-down? Consider social data from Facebook. Likes are a useful piece of data that can be applied both in aggregate and for individual users; but a user liking something is imprecise. It could mean they like it a little, or they love it; it could mean they desire it, or they need it; it could be a passing fancy, or it could indicate imminent action. But which is it? The more granular data can be procured and the more structure it has, the more immediate use online retailers can derive from it. Big data is about connecting the dots of all the content that s out there by analyzing a huge data set and returning a set of results in milliseconds. 14 The solution is one of talent: Retailers also face challenges in finding talent to sort this big data. The engineers who are able to parse these massive amounts of data are hard to come by, and expensive, says Selinger. Data Processing Best Practices Collect as much data as possible; this is where processing starts Crowd wisdom: Even if data cannot be parsed into individual needs and wants, aggregated data can still provide insight into broader trends and generalizations by OSF Global Services. All rights Reserved. Pg. 5

7 It takes expertise: data processing is a specialized, technical field that requires experienced personnel and/or third-party vendors. Implementation Once you ve mined the data, you will have procured highly valuable data. Now it s time to start serving up those personalized recommendations and targeting messaging. But where should personalization techniques be utilized for maximum effect? Personalize everywhere you can throughout the shopping process s Segment your list around products and preferences. Tailor recommended products to recipients. Cross- and up-sell with complementary products. Website Create custom landing pages for promotions. Create custom landing pages for individual customers receiving an , or for repeat customers welcoming them back. Save shopping carts. Display recently viewed, recommend and related products. Let customers save wish lists. Prompt customers to vote on recommendations they like. Customer Support Make sure customer support staff offer up-sells. Have staff reference the customer s history with your site. Packaging Include promotions and related products in shipments. All Devices Don't neglect mobile: If you can see your shopping list on a website, be sure you can get to it on your smartphone. Social Media Use social media to engage with customers by OSF Global Services. All rights Reserved. Pg. 6

8 Monitor/collect relevant data from social media channels (e.g., Facebook likes or Twitter hashtags). Partial Personalization Can Catch Even Anonymous Shoppers True personalization means a recommendation or messaging that s tailored to a particular customer. For example, when you display previously viewed items to a returning shopper, you re customizing their experience in a unique way. It s also possible to partially or pseudo-personalize. For example, James Doman, Marketing Manager for PredictiveIntent, notes that the phrase people who bought this also bought isn t true personalization; nevertheless, it s a way to achieve better-than-random sales results. And sometimes that s the only option you have: it s the closest you can come to personalizing the shopping experience to anonymous shoppers about whom you have little to no data. Logistical considerations When mulling strategies, technologies and vendors to implement personalization for your own ecommerce site, remember to attend to logistical considerations. Technical implementation For example, the technologies that capture data, process it into usable information, and then automatically render personalized search results and recommendations can end up being unwieldy to use, if you re not careful. Polidoro of Ace Tools found a solution that was easy to use: The plug-in lies right on top of my existing system, so I did not have to incur additional IT expenses for maintenance or upgrades. This was key for me to keep the overall expenses down. 16 Privacy concerns Protecting users privacy will be another consideration. Retailers are already experienced in dealing with privacy issues because consumers are increasingly conscious of their data where s it going, and who s using it. They ve proven themselves willing to share data wherever it improves their experience. The key for retailers is to communicate how the data they share with you will make their shopping experience smoother and easier. But, additional data collection also means more attention must be paid to the laws that govern the collection and use of personal information. You do not want to violate your customers trust and privacy by OSF Global Services. All rights Reserved. Pg. 7

9 Summary No two customers are alike, and the online stores that make the effort to cater to their customers individuality stand poised to seize a great measure of market share and profit in the modern digital economy - whether through an integrated data allocation strategy, or something as simple as a recommendation platform and custom product-building tool. We ve seen how the reasoning behind personalization is simple and straightforward, but its actual implementation is not. Partnering with a firm that specializes in integrated ecommerce solutions can remove many of the challenges, but it all starts with identifying the solution that works for your business. Nevertheless, the challenges can be conquered, and once businesses start procuring personal data about their customers, they have the power to boost business across the board: conversion rates, repeat business, cart size, lifetime customer value and more. Online personalization is a key to opening the door to a better shopping experience for your customers and better business performance for you. Personalization through the Buying Cycle: Action Steps Arrival For new visitors, feature products that are trending or commonly searched. For returning visitors, display products they ve viewed before and/or recommendations based on past browsing and purchases. You might consider varying recommendations, information displayed and even pricing based on geographic location. That s actually a relatively common practice internationally. Monitor whether customers leave immediately, or where they go next in the site. Track what catches their eye and interest. Shopping Continue displaying previously viewed items to returning shoppers; they may want to locate a product they viewed previously. Make it easy. Display related products particularly those that seem suited to the individual shopper as recommendations. Don t just point to products; highlight relevant and useful information like product reviews or relevant informational articles you might host on your site by OSF Global Services. All rights Reserved. Pg. 8

10 As visitors browse, monitor their habits and path through the site. What products do they ignore? View? Add to cart? Wish list? Try to procure information about the visitors with their consent but make it organic to the process. Checkout Offer product recommendations related to what s in their cart. This is the place to up-sell and cross-sell. Capture personal preferences and tailor the checkout experience to it. A simple example is saving payment information and offering one-click checkout options. Monitor not just purchases but abandoned items. Follow Up Send post-purchase s with recommended products based on recent purchases or overall behavior on your site. Personalize content, not just recommendations. The more it looks like the is just for the consumer, the better. Consider personalized landing pages for when shoppers click through. Monitor success rates with opens, click-throughs, etc. and tailor future s appropriately. It s possible to get really granular with A/B testing, so you can target text, visuals and content to very distinct groups and even individuals all algorithmically by OSF Global Services. All rights Reserved. Pg. 9

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